A scoping review of clinical decision support systems for child and adolescent mental health
Bibliographic Data
| ID | 21628275 |
|---|---|
| Authors | Lizel‐Antoinette Bertie (0000-0002-8327-9515, Black Dog Institute), Emma McDermott (0000-0001-8149-6164, Black Dog Institute), Juan C Quiroz (0000-0003-0241-5376, UNSW Sydney), Jennifer L Hudson (0000-0001-5778-2670, Black Dog Institute, corresponding author) |
| Year | 2025 |
| Volume | 44 |
| Issue | 4 |
| Pages | 2785-2804 |
| Publication date | 2025-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Current Psychology (JOURNAL) |
| Journal identifiers | ISSN: 1046-1310 • E-ISSN: 1936-4733 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s12144-025-07365-2 |
| OpenAlex | W4406683580 |
| Language | EN |
| Citations received | 1 |
| References cited | 37 |
This scoping review maps the literature on clinical decision support systems (CDSSs) that aid clinicians in treatment decision-making for youth mental health. The objectives were to identify CDSSs used in youth mental health services, as well as grade and evaluate these systems with regard to performance, usability, and clinical utility. Electronic databases were systematically searched for publications related to the development, implementation, or evaluation of clinical decision support systems. Identified CDSSs were grouped according to user setting (primary or mental health care) and three functional areas including screening and assessment, risk prediction, and treatment recommendation. We assessed and graded the systems based on phases of evaluation, as well as the level and direction of evidence. This review identified 10 CDSSs at various stages of development and implementation used across primary and mental health care settings. Of these, one CDSS is in development phase, four have been implemented, and five have evidence of post-implementation investigations. Outside of primary care settings, few CDSSs exist to support clinicians making clinical treatment decisions for youth mental health. Availability of CDSSs is limited and country-specific. In terms of functionality, successful implementation is evident in the functional area of screening and assessment, with more work required in the functional areas of risk prediction and treatment recommendation to assist clinicians in providing youth mental health care. There is potential for machine learning in developing these functional areas
Developmental psychology · Mental health · Psychiatry · Applied Psychology · Clinical Psychology · Digital Mental Health Interventions · Electronic Health Records Systems · Machine Learning in Healthcare · Psychology
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |